Word Sense Disambiguation Based on Center Window

• DOI: 10.4028/www.scientific.net/amr.981.157
• Publication Date: 2014-07-18T07:18:23Z
• Authors: Chun Xiang Zhang; Li Li Guo; Xue Yao Gao
• Keywords: SemEval; Word Sense Disambiguation; Discriminative model; Sliding window protocol

Word sense disambiguation is widely applied to information retrieval, semantic comprehension and automatic summarization. It an important research problem in natural language processing. In this paper, the center window determined from target ambiguous word. The words are extracted as discriminative features. At same time, a new method of word proposed classifier given. optimized tested on SemEval-2007 #Task5 corpus. Experimental results show that accuracy rate arrives at 64.2%.